threshold

摘要： Weeds cause significant production losses estimated at 25%in tropical countries and constitute main factor limiting rice production in Madagascar.This research,which was conducted at Anosibe-Ifanja(Antananarivo,Madagascar),aims to propose the most cost-effective weed management strategies for both irrigated and rainfed rice system to improve rice production.To make the management of these potential rice weeds effective,two cultural practices were tested as good agricultural and farmers’practices on two rice systems.A phytoecological study and a floristic inventory were carried out on test plots,followed by an economic profitability analysis of management strategies.In rainfed rice,a greater number of species were inventoried(42 species in 14 families)than in irrigated rice(37 species in 9 families).The most important families found in both systems were Poaceae and Cyperaceae.But in rainfed rice,two other families are also dominant:Fabaceae and Asteraceae.The study on weed management strategy showed that adoption of in-season and out-of-season tillage combined with regular weeding is effective for weed control in irrigated rice.As far as rainfed rice is concerned,improved farming practice by integrating in-season tillage with aerial ploughing combined with the use of pre-emergence herbicide pendimethalin is more cost-effective.This research has resulted in an in-depth knowledge of rice weeds and weed control strategies that are only feasible with mechanization or animal traction.

摘要： This paper proposes a family of raptor-like rate-compatible spatially coupled low-density parity-check(RL-RC-SC-LDPC)codes from RL-RC-LDPC block codes.There are two important keys.One is the performance of the base matrix.RL-LDPC codes have been adopted in the technical specification of 5G new radio(5G-NR).We use the 5G NR LDPC code as the base matrix.The other is the edge coupling design.In this regard,we have designed a rate-compatible coupling algorithm,which can improve performance under multiple code rates.The constructed RL-RC-SC-LDPC code property requires a large coupling length L and thus we improved the reciprocal channel approximation(RCA)algorithm and proposed a sliding window RCA algorithm.It can provide lower com-plexity and latency than RCA algorithm.The code family shows improved thresholds close to the Shannon limit and finite-length performance compared with 5G NR LDPC codes for the additive white Gaussian noise(AWGN)channel.

摘要： In recent years, the demand for Wireless Sensor Network (WSN) in smart farming has had a tremendous increase in demand for its efficiency. Wireless sensor networks have very many nodes, and it is of no use when the battery dies. This is why there are several routing protocols being take into consideration to cub this problem. In this paper, in order to increase the heterogeneity and energy levels of the network, the M-LEACH protocol is proposed. The key aim of the Leach protocol is to prolong the existence of wireless sensor network by lowering the energy consumption needed for Cluster Head creation and maintenance, the proposed algorithm instructs a node to use high power amplification as it acts as the Cluster heads, and low power amplification when it becomes a Cluster Member, in the next stage. Finally, for better effectiveness, M-LEACH employs hard and soft threshold systems. Since it eliminates collisions and reduces the packet drop ratio for other signals, the M-LEACH protocol proposed works better than the Leach protocol.

摘要： Tropical cyclone extreme rainfall(TCER)causes devastating floods and severe damage in China and it is therefore important to determine its long-term climatological distribution for both disaster prevention and operational forecasting.Based on the tropical cyclone(TC)best-track dataset and TC precipitation data from 1960 to 2019,the spatiotemporal distribution of TCER affecting China is analyzed.Results show that there were large regional differences in the threshold for TCER in China,decreasing from the southeastern coast to the northwest inland.TCER occurred infrequently in northern China but had a high intensity and was highly localized.The frequency and intensity of TCER showed slightly increasing trends over time and was most likely to occur in August(41.0%).Most of the TC precipitation processes with extreme rainfall lasted for four to six days,with TCER mainly occurring on the third to fourth days.TCER with wide areas showed a northwestward prevailing track and a westward prevailing track.Strong TCs are not always accompanied by extreme precipitation while some weak TCs can lead to very extreme rainfall.A total of 64.7%(35.3%)of the TCER samples occurred when the TC was centered over the land(sea).TCER≥250 mm was located within 3°of the center of the TC.When the center of the TC was located over the sea(land),the extreme rainfall over land was most likely to appear on its northwestern(northeastern)side with a dispersed(concentrated)distribution.TCER has unique climatic characteristics relative to the TC precipitation.

摘要： This paper introduces three cosmic expansion models with constant, decelerating and accelerating speed of expansion respectively. Then characters of these cosmic expansion models are compared. Based on these cosmic expansion models, the thresholds of observable universe are calculated via simulations, where the earliest observable cosmic radius R(tearliest) is always 0.368R (R is cosmic radius at current universe time) for any cosmic expansion models.

摘要： Wireless sensor networks(WSNs)have become increasingly popular due to the rapid growth of the Internet of Things.As open wireless transmission media are easy to attack,security is one of the primary design concerns for WSNs.Current solutions consider routing and data encryption as two isolated issues,providing incomplete security.Therefore,in this paper,we divide the WSN communication process into a data path selection phase and a data encryption phase.We propose an improved transmission method based on ant colony optimization(ACO)and threshold proxy re-encryption for WSNs,and we named it as ACOTPRE.The method resists internal and external attacks and ensures safe and efficient data transmission.In the data path selection stage,the ACO algorithm is used for network routing.The improvement of the pheromone concentration is proposed.In order to resist attacks from external attackers,proxy re-encryption is extended to WSN in the data encryption stage.The threshold secret sharing algorithm is introduced to generate a set of re-encryption key fragments composed of random numbers at the source node.We confirm the performance of our model via simulation studies.

摘要： Poisson-Gumbel joint distribution model uses maximum wind speed corresponding to multiple typhoons to construct sample sequence.Thresholds are usually used to filter sample sequences to make them more consistent with Poisson distribution.However,few studies have discussed the threshold setting and its impact on Poisson-Gumbel joint distribution model.In this study,a sample sequence based on the data of Qinzhou meteorological station from 2005 to 2018 were constructed.We set 0%,5%,10%,20%and 30%gradient thresholds.Then,we analyzed the influence of threshold change on the calculation results of maximum wind speed in different return periods.The results showed that:(1)When the threshold increases,the maximum wind speed of each return period will decrease gradually.This indicates that the length of the sample series may have a positive effect on the return period wind speed calculation in Gumbel and Poisson-Gumbel methods.Although the augment of the threshold increases the average value of the maximum wind speed of the sample sequence,it shortens the length of the sample sequence,resulting in a lower calculated value of the maximum wind speed.However,this deviation is not large.Taking the common 10%threshold as an example,the maximum wind speed calculation deviation in the 50 a return period is about 1.9%;(2)Theoretically,the threshold is set to make the sample sequence more consistent with Poisson distribution,but this example showed that the effect is worth further discussion.Although the overall trend showed that the increase of the threshold can makeχ2 decrease,the correlation coefficient of linear fitting was only 0.182.Taking Qinzhou meteorological station data as an example,theχ2 of 20%threshold was as high as 6.35,meaning that the selected sample sequence was not ideal.

摘要： The internet of things(IoT)has a wide variety of applications,which in turn raisesmany challenging issues.IoT technology enables devices to closely monitor their environment,providing context-aware intelligence based on the real-time data collected by their sensor nodes.The IoT not only controls these devices but also monitors their user’s behaviour.One of the major issues related to IoT is the need for an energy-efficient communication protocol which uses the heterogeneity and diversity of the objects connected through the internet.Minimizing energy consumption is a requirement for energyconstrained nodes and outsourced nodes.The IoT nodes deployed in different geographical regions typically have different energy levels.This paper focuses on creating an energy-efficient protocol for IoTwhich can deal with the clustering of nodes and the cluster head selection process.An energy thresholdmodel is developed to select the appropriate cluster heads and also to ensure uniform distribution of energy to those heads andmember nodes.The proposed model envisages an IoT network with three different types of nodes,described here as advanced,intermediate and normal nodes.Normal nodes are first-level nodes,which have the lowest energy use;intermediate nodes are second-level nodes,which have a medium energy requirement;and the advanced class are thirdlevel nodes with the highest energy use.The simulation results demonstrate that the proposed algorithm outperforms other existing algorithms.In tests,it shows a 26%improvement in network lifetime compared with existing algorithms.

摘要： Radio frequency interference (RFI) is greatly harmful to Global Navigation Satellite System (GNSS) receivers. Sweep interference is one of the RFI for the GNSS receivers, which can degrade the performance of GNSS receivers seriously. In this paper, the Fractional Fourier Transform (FrFT) of time-frequency analysis is proposed in the GNSS interference detection and suppression. The FrFT method is tested for detecting and suppressing sweep interference, which is generated by a GNSS jammer. In the simulation experiment, the GNSS signal affected by sweep frequency interference is successfully captured after interference suppression by using the proposed method, which shows its effectiveness. The interference detection performance of the FrFT method is compared with the conventional techniques such as Short-Time Fourier transform (STFT) and Wigner-Ville distribution (WVD). The detection performance is improved by about a least one order of magnitude. In the aspect of interference suppression, a threshold method based on detection probability is proposed, and the performance of the proposed threshold method is compared with the conventional threshold methods. In the result, the interference tolerance is increased by 5 dB compared with the mean threshold method, and by 9 dB compared with the fixed threshold.

摘要： Based on the data of the cases of severe convection weather such as hail,thunderstorm(thunderstorm gale)and short-time heavy precipitation in recent 10 years,the spatial and temporal distribution characteristics of different types of severe convection weather were analyzed.The results show that the frequency of severe convection weather tended to increase,of which short-time heavy precipitation and thunderstorm weather rose,and hail and thunderstorm gale weather decreased.Severe convection weather began to extend in late spring and early autumn.Typical cases were selected to analyze the evolution mechanism,and the conceptual models of severe convective weather caused by cold advection forcing,warm advection forcing and baroclinic frontogenesis were obtained.The key predictors for the potential prediction of severe convection weather were proposed,such as CAPE(convective available potential energy)for hail weather,UH index(maximum ascending helicity)for thunderstorm gale and PWV(precipitable water vapor)for short-time heavy precipitation.ERA5 data were used to get the forecast threshold of the key factor of classified severe convection weather,and it was verified that the threshold was available.Meanwhile,the causes of the error of failure cases were analyzed.For instance,the larger deviation of CAPE was caused by the 2 m deviation of temperature.Supplementary correction method and threshold were given to provide a reference for the objective forecast and early warning of severe convection weather.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.

摘要： Data Stream (Time series database) has been widely used in aspect of Web monitor and sensor net. Mining on data streams has been a brand new research field in recent years, as the representation of data streams turned to be the critical problem of this field. In this paper, we propose a novel segmentation algorithm, which can represented data stream in an effective and compact fashion. We first introduce the general view of Piecewise Linear Representation which represents data streams, typical segment algorithms on data streams and their features. After that, we present some ideas on improving performance and compress efficiency of segmentation algorithm using PLR, and introduce a fast Sliding Window based algorithm on data stream segmentation using linear regression. Detailed experiments have been conducted to evaluate the performance of proposed method, and the results show the superiority of our algorithm.